A greedy data-anchored placement of microservices in federated clouds

n a multiple cloud environment, the placement of execution environments is crucial and may be subject to data constraints. Data could be anchored to some environments due to regulatory compliance, data sovereignty issues, or performance optimization. Consequently, applications and microservices must be designed to operate efficiently with these constraints. This en- forces specific placement strategies to obtain good performances and scalability. This paper proposes a technique to enforce a constrained data-centric deployment placement in a federated multi-cloud environment. The algorithm analyzes a graph model of microservices interaction, considering communication with data storage and adopting “anchors” for implementing a data- centric placement strategy. The results show how a better placement based on data position in multiple clouds improves performance in terms of overall system response time. This also allows microservices to offload near data sources for multi-cloud environments, improving overall system performance without violating data movement constraints.